Commit f2bba405 authored by Alexis Brenon's avatar Alexis Brenon
Browse files

馃敡 Use a pre-trained agent on real data

Use a max tries value of 3 to simulate user patience
parent 3a858096
......@@ -30,65 +30,22 @@ local args = {
class = "smarthome.sweethome.GraphicalAnnotatedSweetHome",
params = {
map_path = paths.concat("assets", "domus_inferred.svg"),
max_tries = 1,
data_path = paths.concat('data', 'SweetHomeInferred'),
max_tries = 3,
},
},
testing_environment = {
class = "smarthome.sweethome.GraphicalAnnotatedSweetHome",
params = {
map_path = paths.concat("assets", "domus_inferred.svg"),
max_tries = 1,
data_path = paths.concat('data', 'SweetHomeInferred-test'),
max_tries = 3,
},
},
-- Agent
agent = {
class = "NeuralQLearner",
params = {
preprocess = {
class = "Downsample",
params = {
scale_size = {84,84}
},
},
inference = {
class = "Inference",
params = {
input_size = {1, 84, 84},
conv_layers = {
{
n_filters = 32,
field_size = {width = 8, height = 8},
stride = {width = 4, height = 4},
zero_padding = {width = 0, height = 0}
},
{
n_filters = 64,
field_size = {width = 4, height = 4},
stride = {width = 2, height = 2},
zero_padding = {width = 0, height = 0}
},
{
n_filters = 64,
field_size = {width = 3, height = 3},
stride = {width = 1, height = 1},
zero_padding = {width = 0, height = 0}
}
}
},
},
memory = {
pool_size = 100,
},
learn_start = 50,
target_q = 100,
update_freq = 1,
minibatch_size = 32,
ep_start = 1,
ep_end = 0.5,
ep_endt = 100000,
}
file = paths.concat('outputs', 'agent-synthetic-annot-1.t7')
},
-- Experiment
......
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